The present invention, in some embodiments thereof, relates to monitoring and, more particularly, but not exclusively, to a method and system for behavioral monitoring.
Systems that employ cellular phones for monitoring subjects are known and found, for example, in U.S. Pat. No. 8,181,113; U.S. Patent Application Publication No. 20140052475; Campbell et al., 2012, “From Smart to Cognitive Phones,” IEEE pervasive computing; Pentland et al., 2009, “Using Reality Mining to Improve Public Health and Medicine,” A Whitepaper Commissioned by the Robert Wood Johnson Foundation; and LiKamWa et al., 2013, “MoodScope: Building a Mood Sensor from Smartphone Usage Patterns,” in MobiSys 2013, The 11th International Conference on Mobile Systems, Applications, and Services, Taipei, Taiwan.
For example, U.S. Pat. No. 8,181,113 discloses a software facility that exchanges information between sources of context data and consumers of context data. A characterization module operating in a wearable computer system receives context information from one or more context servers, and provides that information to one or more context clients. The context information represents a context of the wearable, the user of the wearable, the surrounding physical environment and/or the available electronic data environment. Attributes are used for modeling aspects of the context.
U.S. Patent Application Publication No. 20140052475 discloses a method for supporting a subject through a treatment regimen. A log of use of a native communication application executing on a mobile computing device by the subject within a time period is accessed, and a survey response corresponding to the time period is received from the subject. An adherence to the treatment regimen by the subject within the time period is estimated based on the survey response. The log is correlated with the adherence to the treatment regimen. The process is repeated and a subject regimen adherence model comprising the logs of use of the native communication application and the adherences is generated. A third log of use of the native communication application is accessed and the adherence to the treatment regimen is estimated based on the subject regimen adherence model and the third log.
Campbell et al. disclose a mobile health app that can automatically monitor and promote multiple aspects of physical and emotional well-being. The app continuously tracks user behaviors along three distinct health dimensions without requiring user input. Classification algorithms run directly on the phone to automatically infer the user's estimated sleep duration, physical activity, and social interaction.